Machine Learning Engineer
Core
Designing and developing highly scalable real-time data systems and full-stack applications to ingest, transform, and operationalize multi-modal data (image, audio, video, documents) using Hadoop ecosystem components and machine learning frameworks.
Role type
Senior Machine Learning Engineer (Data Infrastructure & Full-Stack)
Builds
Scalable real-time data pipelines, data ingestion/transformation frameworks, and internal engineering tools for multi-modal data.
Domain
Big Data Infrastructure, Machine Learning Operations, Full-Stack Development
Deliverable
production ML models | product features | infrastructure
Required skills
Python, Java, Scala, C++, XGBoost, Scikit-learn, TensorFlow/Keras, Hugging Face, Hadoop ecosystem (Iceberg, Spark, Ozone, Trino, Hive, Ranger, Kafka, Flink, NiFi), Cloudera Machine Learning (CML), Spark MLlib, Flask, React, Shell scripting, Performance optimization, Data engineering
Preferred skills
Experience with multi-modal data (image, audio, video, unstructured documents), Real-time system architecture, Model deployment
Technologies
Hadoop, Iceberg, Spark, Ozone, Trino, Hive, Ranger, Kafka, Flink, NiFi, Cloudera Machine Learning (CML), XGBoost, Scikit-learn, TensorFlow, Keras, Hugging Face, Flask, React
Responsibilities
Design and develop highly scalable real-time systems using Hadoop ecosystem components; Build robust data ingestion and transformation frameworks for multi-modal data; Develop full-stack applications and internal engineering tools; Collaborate with data scientists to operationalize machine learning models; Perform performance tuning and optimization of data applications on Hadoop.
Seniority
Senior, hands-on IC